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Data:
1.41 1.43 1.43 1.45 1.49 1.54 1.54 1.55 1.55 1.55 1.55 1.56 1.56 1.59 1.62 1.62 1.64 1.65 1.64 1.65 1.65 1.65 1.66 1.67 1.68 1.68 1.68 1.71 1.71 1.71 1.71 1.71 1.72 1.79 1.8 1.8 1.84 1.9 1.9 1.92 1.93 1.93 1.94 1.94 1.95 1.95 1.96 1.95 1.95 1.94 1.94 1.93 1.93 1.9 1.91 1.9 1.91 1.91 1.91 1.91 1.93 1.94 1.93 1.91 1.88 1.88 1.89 1.9 1.92 1.93 1.96 1.96
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R Code
par3 <- '0.1' par2 <- '0.99' par1 <- '0.01' par1 <- as(par1,'numeric') par2 <- as(par2,'numeric') par3 <- as(par3,'numeric') library(Hmisc) myseq <- seq(par1, par2, par3) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) bitmap(file='test1.png') plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'quantiles',header=TRUE) a<-table.element(a,'value',header=TRUE) a<-table.element(a,'standard error',header=TRUE) a<-table.row.end(a) length(hd) for (i in 1:length(hd)) { a<-table.row.start(a) a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE) a<-table.element(a,as.matrix(hd[i])[1,1]) a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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